Introduction to TensorFlow

For the final Exercise, I did this but I am not able to understand the error, due to which I am not able to complete the last part

for (minibatch_X, minibatch_Y) in zip(X_train, Y_train):
# Select a minibatch
with tf.GradientTape() as tape:
# 1. predict
Z3 = forward_propagation(minibatch_X, parameters)
# 2. loss
minibatch_cost = compute_cost(Z3, minibatch_Y)

        trainable_variables = [W1, b1, W2, b2, W3, b3]
        grads = tape.gradient(minibatch_cost, trainable_variables)
        optimizer.apply_gradients(zip(grads, trainable_variables))
        epoch_cost += minibatch_cost / minibatch_size

If someone can help me with it, it can be very helpful.

Thank you

Hi, @Saransh_Jhunjhunwala.

What error did you get? Bear in mind that you don’t have to make any changes to the model function.

Fixed by @Saransh_Jhunjhunwala.

Re-running the notebook solved the problem.

Good luck with the rest of the course :slight_smile: